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  • Dynamics of adult neurogenesis in the hippocampus I
2004
2005
Dynamics of adult neurogenesis in the hippocampus I
Collaborator: Elena Beißwanger, Christoph Bandt, Gerd Kempermann

The dentate gyrus in the hippocampus is one of the few regions in the brain where significant numbers of new neurons are generated in the adult brain. In this project we have started to develop a model of the dynamics of cell generation based on experimental data from Gerd Kempermann et al, who have characterized different cell types in the neurogensis process, see figure 1, and have measured correponding cell populations over time.

Figure 1: Cell types in the neurogenesis process that are distinguished by different markers. (Kempermann et al.)

Based on the experimentally determined cell types, we have developed a dynamic model that simulates neurogenesis. The model is largely linear but incorporates bleaching of cells (cells loose their markers by dividing into two) as an additional nonlinear effect.

Figure 2: Model of the dynamics of neurogenesis. Boxes indicate cell populations that are in the S-phase of cell division; circles indicate cell populations that are not. In this model we differentiate only four cell types, only the first three of which can actually divide.

In the end we did not have enough data to sufficiently constrain the model, but the model helped us to get a clear picture of the neurogenesis process and to design new experiments that would provide enough data. The project entered a second phase when this additional data was available, see Regulation of adult neurogenesis in the hippocampus II.

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

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